The Basics of Factorial & Crossover

TrialsPatrick B. Barlow

PhD Candidate in Evaluation, Statistics, & Measurement

The University of Tennessee

In This Presentation

• Factorial Trials

• What are they?

• When are they used?

• Example…

• Crossover Trials

• What are they?

• When are they used?

• Example…

• Possible Issues with These Designs

• Common Threats to Internal Validity

Factorial DesignsWhat are they?

When are they used?

Example…

What are They?

• Factorial designs allow for researchers to test multiple interventions or treatment combinations in a single study.

• For example: drug A or Drug B and 3x per week or everyday dose cycle.

• The simplest form of this design is a 2x2 factorial design.

• Allows researchers to test individual treatment effects and/or interactions between different treatments.

• Looks like a “grid”

Why are They Used?

• Factorial design are commonly used to effectively test multiple treatments in a single study.

• More efficient and more statistically powerful than multiple single intervention studies

• Especially useful for testing interactions among different interventions or treatments

Example

Dose CycleStatin

Rosuvastatin (Crestor)

Atorvastatin (Lipitor)

3x Per Week M LDL M LDL

Everyday M LDL M LDL

What is the effect of dose (3x pw or everyday) and statin (Rusuvastatin or Atorvastatin) regimen on mean LDL Cholesterol?

Why be so Complicated?

• Using a more complicated design gives the researcher several advantages:

• Reduced statistical error

• Ability to look at complex relationships

• Can control for confounders

• Allows for a more complete and in-depth interpretation of the phenomenon. No phenomenon you study exists in a vacuum!

Crossover DesignsWhat are they?

When are they used?

Example…

What are They?

• A cross-over trial design involves giving the two or more interventions/treatments to a single group of patients.

• At its most basic, this trial tests the efficacy of two treatments where each patient spends a period of time under both treatment options.

• Patients are randomized into which treatment they receive first, and then swap to the other treatment after a predetermined time.

What are They?

A

B“Crossov

er”

A

B

Why are They Used?

• Cross-over trials are useful because they reduce confounding factors associated with between-subjects designs.

• Patients serve as their own controls

• Useful for time-dependent research questions

• Higher statistical power than between subjects designs due to no between-subjects error (i.e. need less patients to find statistical significance).

Example

3x Per Week

Treatment

Everyday Treatment

Everyday Treatment

3x Per Week

Treatment

Week Six

Weaknesses with These DesignsCommon threats to internal validity that can tarnish these “gold

standard” designs

Internal vs. External Validity

• One of the strengths of randomized designs are that they have substantially higher internal & external validity.

• Internal Validity: refers to the integrity of the experiment itself. It is the ability to draw a causal link between your treatment and the dependent variable of interest.

• External Validity: by contrast, refers to the ability to generalize your study findings to the population at large. In other words, are your findings from a sample of UTMCK patients with HTN going to apply to all patients with HTN?

Threats to Internal Validity

• Shadish, Cook & Campbell (2002) summarized a number of possible threats to internal validity, which can severely jeopardize the findings of even RCT designs. In particular:

• History, Mortality, & Maturation

• Repeated Testing

• Confounding

• Diffusion & Compensatory Rivalry

Threats to Internal Validity

• History, Mortality, & Maturation

• History: events external to the experiment influence the participants’. EX: Superstorm Sandy hits during a crossover trial in New Jersey.

• Mortality: Patients either die (mortality) or drop out of the study (attrition) at different rates.

• Maturation: Patients change over the course of the treatment, which influences results. EX: Children grow up during the course of a pediatric clinical trial.

• Repeated Testing

• Patients can become “test-wise” if given the same subjective test multiple times, or they become conditioned to being tested (EX: patient’s pulse increases before a needle stick).

Threats to Internal Validity

• Confounding

• Uncontrolled variables are interacting with treatment effects, which can produce spurious or “random” associations/results.

• Diffusion & Compensatory Rivalry

• Diffusion: Treatment effects can “spill over” or “spread” across treatment groups. EX: Patients from different groups live near each other and discuss / share their experiences or treatments.

• Compensatory Rivalry: Patients perform in a certain way because they know they’re in the control / experimental groups.

Questions?

Additional Resources• Factorial Trials:

• Article Explaining the design and presentation of factorial trials (free use): http://www.biomedcentral.com/1471-2288/3/26

• Crossover Trials

• Design and use of cross-over trials electronic book chapter (available through UTMCK login) http://www.sciencedirect.com/science/article/pii/S0169716107270154